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Abstract

To reveal the relationships between large-scale, heterogeneous biochemical networks and their associated functions, called design principles in biology, it is critically important to disintegrate the networks into topology- or function-based subnetworks to analyze the mechanism of how each subnetwork generates a specific biological function, and to synthesize them as the whole system in the same manner as engineering, where a variety of parts are assembled into functional machines. This synthesis and analysis approach can be carried out by a computer. In this review, the author describes several methodologies that serve to disintegrate biological systems into biologically meaningful modules, with practical consequences for systems biology studies.

Large-Scale Protein-Protein Interaction Networks

Many complex networks are naturally divided into modules in which the links within the modules are much more dense than those across the modules. Cellular functions are typically organized in a hierarchical modular architecture, where each module is a discrete object composed of a group of tightly linked components (genes, proteins, and metabolites) and performs a relatively independent task.

Protein-protein interaction (PPI) networks are appealing to biologists wishing to understand a complete and interconnected picture of cellular function. PPI networks can generally be transformed into a graph where a node is specified as a given protein with a given interaction at its edge. A large size and substantial heterogeneity are common features of PPI networks. In typical PPI networks, a few nodes may have a high degree of interconnectedness, while others may have very few interactions. Classical graph-based agglomerative methods employ a variety of similarity measures between nodes to partition PPI networks, but they often result in a poor clustering arrangement that contains only one or a few giant core clusters with many smaller ones (Barabasi & Oltvai, 2004).